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Controlling light propagation through complex media plays a significant role in a wide range of applications ranging from astronomical observations to microscopy. Although, several advances have been made based on adaptive optics, optical phase conjugation and wavefront shaping, but many of these involve challenges. Recently, controlling light propagation in complex media by simply structuring light has shown promising capabilities. We present experimental and numerical investigations of abruptly autofocusing of circular Airy derivative beams (CADBs) in complex media. We find that up to a relatively high turbulence strength, CADB possesses relatively good abrupt autofocusing, however, efficiency and autofocusing position vary with the strength of turbulence. Further, the spatial distortions in CADB caused by turbulence are quantified by an overlap integral, which shows that CADB possesses reasonably good resilience against the turbulence. The diffraction efficiency of CADB changes by a factor of ~ 1.7 with increasing strength of turbulence from zero to high, indicating good confinement of intensity at autofocusing. The focused beam spot size grows gradually with increasing the strength of turbulence, specifically, it grows by a factor of ~ 2 for a strong turbulence, indicating reasonably good focusing abilities. The results of CADB are compared with a Gaussian beam, and find that CADB possesses superior focusing abilities in turbulent media. We have carried out a detailed analysis of these observations based on Zernike polynomials, which reveals that different kinds of aberrations present in turbulent media leads to distortions in the spatial structure as well as other properties of CADBs. Our results can be used for various applications, such as in biomedical treatment, seismology, optical tweezers and material processing., Comment: 20 pages, 23 figures

We present JWST NIRSpec observations in IFS mode of the galaxy GS5001 at redshift z=3.47, the brightest member of a candidate protocluster in the GOODS-S field. The data cover a field of view (FoV) of 4''$\times$4'' (~$30\times30$~kpc$^2$) and were obtained as part of the GA-NIFS GTO program. The observations include both high (R~2700) and low (R~100) spectral resolution data, spanning the rest-frame wavelength ranges 3700-6780A and 1300-11850A, respectively. We analyse the spatially resolved ionised gas kinematics and interstellar medium properties, including obscuration, gas metallicity, excitation, ionisation parameter, and electron density. In addition to the central galaxy, the NIRSpec FoV covers three components in the south, with velocities blue-shifted by -150 km/s with respect to the main galaxy, and another source in the north redshifted by ~200 km/s. The emission line ratios in the BPT diagram are consistent with star formation for all the sources in the FoV. We measure electron densities of ~500 cm$^{-3}$ in the different sources. The gas-phase metallicity in the main galaxy is 12+log(O/H) $= 8.45\pm0.04$, and slightly lower in the companions (12+log(O/H)$ = 8.34-8.42$), consistent with the mass-metallicity relation at $z\sim3$. We find peculiar line ratios (high log [NII]/H$\alpha$, low log [OIII]/H$\beta$) in the northern part of the main galaxy (GS5001). These could be attributed to either higher metallicity, or to shocks resulting from the interaction of the main galaxy with the northern source. We identify a spatially resolved outflow in the main galaxy, with an extension of about 3 kpc. We find maximum outflow velocities of ~400 km/s, an outflow mass of $(1.7\pm0.4)\times 10^8$ M$_{\odot}$, a mass outflow rate of $23\pm5$ M$_{\odot}$ yr$^{-1}$ and a mass loading factor of 0.23. These properties are compatible with star formation being the driver of the outflow., Comment: Submitted to A&A

Recent advancements in Artificial Intelligence (AI), particularly the widespread adoption of Large Language Models (LLMs), have significantly enhanced text analysis capabilities. This technological evolution offers considerable promise for automating the review of scientific papers, a task traditionally managed through peer review by fellow researchers. Despite its critical role in maintaining research quality, the conventional peer-review process is often slow and subject to biases, potentially impeding the swift propagation of scientific knowledge. In this paper, we propose RelevAI-Reviewer, an automatic system that conceptualizes the task of survey paper review as a classification problem, aimed at assessing the relevance of a paper in relation to a specified prompt, analogous to a "call for papers". To address this, we introduce a novel dataset comprised of 25,164 instances. Each instance contains one prompt and four candidate papers, each varying in relevance to the prompt. The objective is to develop a machine learning (ML) model capable of determining the relevance of each paper and identifying the most pertinent one. We explore various baseline approaches, including traditional ML classifiers like Support Vector Machine (SVM) and advanced language models such as BERT. Preliminary findings indicate that the BERT-based end-to-end classifier surpasses other conventional ML methods in performance. We present this problem as a public challenge to foster engagement and interest in this area of research.

The electronic, structural, optical, and thermoelectric properties of the Cs2O cubic structure have been investigated using density functional theory (DFT). The calculations utilize a full relativistic version of the full-potential augmented plane-wave plus local orbitals method, which is based on density functional theory, employing both the GGA and LDA approximations. Additionally, we employed the GGA proposed by Trans-Blaha (GGA-mBJ) for band structure computations, revealing the indirect band gap nature of Cs2O. The optical properties are also addressed by computing the refractive index, extinction coefficient, and complex dielectric tensor. The electrical conductivity, Seebeck coefficient, and thermal conductivity exhibit temperature-dependent variations, indicating the formation of a thermoelectric material. Our findings indicate that the compound under investigation is categorized as a p-type semiconductor, with the majority of charge carriers responsible for conduction being holes rather than electrons., Comment: 21 pages

This paper presents an investigation of spectral properties of 10 millisecond pulsars (MSPs) discovered by the uGMRT, observed from 2017-2023 using band 3 (300-500 MHz) and 4 (550-750 MHz) of uGMRT. For these MSPs, we have reported a range of spectral indices from ~0 to -4.8, while averaging the full observing band and all the observing epochs. For every MSP, we calculated the mean flux densities across 7-8 sub-bands each with approximately 25 MHz bandwidth spanning band 3 and band 4. We computed their modulation indices as well as average and maximum-to-median flux densities within each subband. Using a temporal variation of flux density we calculated the refractive scintillation time scales and estimated structure function with time lag for 8 MSPs in the sample. We note a significant temporal evolution of the in-band spectra, classified into three categories based on the nature of the best-fit power-law spectra, having single positive spectral indices, multiple broken power law, and single negative spectral indices. Additionally, indications of low-frequency turnover and a temporal variation of the turnover frequency (to the extent that turnover was observed for some of the epochs while not seen for the rest) were noted for all the MSPs. To the best of our knowledge, this is the first systematic investigation probing temporal changes in the MSP spectra as well as in turnover frequency. Future exploration with dense monitoring combined with modeling of spectra can provide vital insight into the intrinsic emission properties of the MSPs and ISM properties., Comment: 18 Pages, 8 Figures, 3 Tables. Accepted for Publication in ApJ

Decameter hectometric (DH; 1-14 MHz) type-IV radio bursts are produced by flare-accelerated electrons trapped in post-flare loops or the moving magnetic structures associated with the CMEs. From a space weather perspective, it is important to systematically compile these bursts, explore their spectro-temporal characteristics, and study the associated CMEs. We present a comprehensive catalog of DH type-IV bursts observed by the Radio and Plasma Wave Investigation (WAVES) instruments onboard Wind and STEREO spacecraft, covering the period of white-light CME observations by the Large Angle and Spectrometric Coronagraph (LASCO) onboard the SOHO mission between November 1996 and May 2023. The catalog has 139 bursts, of which 73% are associated with a fast (>900 km/s) and wide (>60$^o$) CME, with a mean CME speed of 1301 km/s. All DH type-IV bursts are white-light CME-associated, with 78% of the events associated with halo CMEs. The CME source latitudes are within $\pm$45$^o$. 77 events had multi-vantage point observations from different spacecraft, letting us explore the impact of line of sight on the dynamic spectra. For 48 of the 77 events, there was good data from at least two spacecraft. We find that, unless occulted by nearby plasma structures, a type-IV burst is best viewed when observed within $\pm$60$^o$ line of sight. Also, the bursts with a duration above 120 min, have source longitudes within $\pm$60$^o$. Our inferences confirm the inherent directivity in the type-IV emission. Additionally, the catalog forms a sun-as-a-star DH type-IV burst database., Comment: 18 pages, 12 figures, Accepted in ApJ on 31 May, 2024

The structural, electronic, and dielectric (optical) properties of graphene-like 2D MgO monolayer have been explored through first-principles calculations under bi-axial tensile and compressive mechanical strain within a range of -10% to +10%. Our findings revealed that the pristine MgO monolayer is an indirect band gap semiconducting material and the semiconducting mature of MgO monolayer remains consistent under both compressive and tensile mechanical strain. This nature of MgO is confirmed through partial density of states (PDOS) as well as electronic band structure. PDOS exhibits the contribution of different atomic orbitals in bond formation and nature of bond, while band structure provides insight into electron transitions between energy levels of valance and conduction bands. All optical parameters (dielectric function, reflectivity, energy loss, refractive index, extinction coefficient and absorption) are plotted in an energy range 0-15 eV. Within this energy interval, MgO possesses the highest value of the refractive index (2.13) at 3.12 eV energy. Also, a detailed analysis of changes in the geometrical structure of MgO monolayer is provided., Comment: 6 figures

JWST is discovering increasing numbers of quiescent galaxies 1--2 billion years after the Big Bang, whose redshift, high mass, and old stellar ages indicate that their formation and quenching were surprisingly rapid. This fast-paced evolution seems to require that feedback from AGN (active galactic nuclei) be faster and/or more efficient than previously expected \citep{Xie24}. We present deep ALMA observations of cold molecular gas (the fuel for star formation) in a massive, fast-rotating, post-starburst galaxy at $z=3.064$. This galaxy hosts an AGN, driving neutral-gas outflows with a mass-outflow rate of $60\pm20$ M$_{\odot}$ yr$^{-1}$, and has a star-formation rate of $<5.6$ M$_{\odot}$ yr$^{-1}$. Our data reveal this system to be the most distant gas-poor galaxy confirmed with direct CO observations (molecular-gas mass $< 10^{9.1}$ M$_{\odot}$; <0.8 % of its stellar mass). Combining ALMA and JWST observations, we estimate the gas-consumption history of this galaxy, showing that it evolved with net zero gas inflow, i.e., gas consumption by star formation matches the amount of gas this galaxy is missing relative to star-forming galaxies. This could arise both from preventive feedback stopping further gas inflow, which would otherwise refuel star formation or, alternatively, from fine-tuned ejective feedback matching precisely gas inflows. Our methods, applied to a larger sample, promise to disentangle ejective vs preventive feedback., Comment: 14 pages, 4 figures

The first observations of JWST have revolutionized our understanding of the Universe by identifying for the first time galaxies at $z\sim13$. In addition, the discovery of many luminous galaxies at Cosmic Dawn ($z>10$) has suggested that galaxies developed rapidly, in apparent tension with many standard models. However, most of these galaxies lack spectroscopic confirmation, so their distances and properties are uncertain. We present JADES JWST/NIRSpec spectroscopic confirmation of two luminous galaxies at redshifts of $z=14.32^{+0.08}_{-0.20}$ and $z=13.90\pm0.17$. The spectra reveal ultraviolet continua with prominent Lyman-$\alpha$ breaks but no detected emission lines. This discovery proves that luminous galaxies were already in place 300~million years after the Big Bang and are more common than what was expected before JWST. The most distant of the two galaxies is unexpectedly luminous and is spatially resolved with a radius of 260 parsecs. Considering also the very steep ultraviolet slope of the second galaxy, we conclude that both are dominated by stellar continuum emission, showing that the excess of luminous galaxies in the early Universe cannot be entirely explained by accretion onto black holes. Galaxy formation models will need to address the existence of such large and luminous galaxies so early in cosmic history., Comment: 15 figures, 3 tables, published in Nature

The article studies the different physical, vibrational, nonlinear optical, and thermodynamical properties of higher homologs 5O.m (m = 14,16) liquid crystalline compounds using density functional theory. The optimized structure of 5O.m (m= 14,16) liquid crystals was obtained by using density functional theory (DFT) with B3LYP functional and standard basis set 6-31G (d, p). The Infrared spectra (IR), various physical properties such as HOMO-LUMO, nonlinear optical properties (NLO), reactivity parameters, relative energy gaps, and electrostatic potential function are computed and analyzed using the optimized structure of 5O liquid crystal. The time-dependent density functional theory (TD-DFT) has been used to analyze and obtain UV-Vis spectra for both LC compounds. It is observed that the 5O.m (m=14,16) liquid crystals are showing the lower value of HOMO-LUMO energy gaps as 4.17ev which resulted in some highly fascinating optical and physical properties. Using DFT excellent agreement is observed between all spectrum patterns and the simulated UV-Vis and IR spectra. This article, however, also discussed temperature-dependent thermodynamical properties such as zero-point vibrational energy (ZPVE), total thermal energy, total specific heat capacity, rotational constants, and total entropy which enable us to understand the phase transition behavior and specific transition temperatures of different phases, Comment: 24 Pages, 7 figures

The Orion Molecular Cloud complex, one of the nearest (D = 406 pc) and most extensively studied massive star-forming regions, is ideal for constraining the physics of stellar feedback, but its ~12 deg diameter on the sky requires a dedicated approach to mapping ionized gas structures within and around the nebula. The Sloan Digital Sky Survey (SDSS-V) Local Volume Mapper (LVM) is a new optical integral field unit (IFU) that will map the ionized gas within the Milky Way and Local Group galaxies, covering 4300 deg^2 of the sky with the new LVM Instrument. We showcase optical emission line maps from LVM covering 12 deg^2 inside of the Orion belt region, with 195,000 individual spectra combined to produce images at 0.07 pc (35.3") resolution. This is the largest IFU map made (to date) of the Milky Way, and contains well-known nebulae (the Horsehead Nebula, Flame Nebula, IC 434, and IC 432), as well as ionized interfaces with the neighboring dense Orion B molecular cloud. We resolve the ionization structure of each nebula, and map the increase in both the [SII]/Ha and [NII]/Ha line ratios at the outskirts of nebulae and along the ionization front with Orion B. [OIII] line emission is only spatially resolved within the center of the Flame Nebula and IC 434, and our ~0.1 pc scale line ratio diagrams show how variations in these diagnostics are lost as we move from the resolved to the integrated view of each nebula. We detect ionized gas emission associated with the dusty bow wave driven ahead of the star sigma Orionis, where the stellar wind interacts with the ambient interstellar medium. The Horsehead Nebula is seen as a dark occlusion of the bright surrounding photo-disassociation region. This small glimpse into Orion only hints at the rich science that will be enabled by the LVM., Comment: 13 pages, 10 figures, accepted for publication in A&A

Semi-supervised medical image segmentation has gained growing interest due to its ability to utilize unannotated data. The current state-of-the-art methods mostly rely on pseudo-labeling within a co-training framework. These methods depend on a single pseudo-label for training, but these labels are not as accurate as the ground truth of labeled data. Relying solely on one pseudo-label often results in suboptimal results. To this end, we propose a novel approach where multiple pseudo-labels for the same unannotated image are used to learn from the unlabeled data: the conventional fixed pseudo-label and the newly introduced dynamic pseudo-label. By incorporating multiple pseudo-labels for the same unannotated image into the co-training framework, our approach provides a more robust training approach that improves model performance and generalization capabilities. We validate our novel approach on three semi-supervised medical benchmark segmentation datasets, the Left Atrium dataset, the Pancreas-CT dataset, and the Brats-2019 dataset. Our approach significantly outperforms state-of-the-art methods over multiple medical benchmark segmentation datasets with different labeled data ratios. We also present several ablation experiments to demonstrate the effectiveness of various components used in our approach., Comment: Under Review

The malware booming is a cyberspace equal to the effect of climate change to ecosystems in terms of danger. In the case of significant investments in cybersecurity technologies and staff training, the global community has become locked up in the eternal war with cyber security threats. The multi-form and changing faces of malware are continuously pushing the boundaries of the cybersecurity practitioners employ various approaches like detection and mitigate in coping with this issue. Some old mannerisms like signature-based detection and behavioral analysis are slow to adapt to the speedy evolution of malware types. Consequently, this paper proposes the utilization of the Deep Learning Model, LSTM networks, and GANs to amplify malware detection accuracy and speed. A fast-growing, state-of-the-art technology that leverages raw bytestream-based data and deep learning architectures, the AI technology provides better accuracy and performance than the traditional methods. Integration of LSTM and GAN model is the technique that is used for the synthetic generation of data, leading to the expansion of the training datasets, and as a result, the detection accuracy is improved. The paper uses the VirusShare dataset which has more than one million unique samples of the malware as the training and evaluation set for the presented models. Through thorough data preparation including tokenization, augmentation, as well as model training, the LSTM and GAN models convey the better performance in the tasks compared to straight classifiers. The research outcomes come out with 98% accuracy that shows the efficiency of deep learning plays a decisive role in proactive cybersecurity defense. Aside from that, the paper studies the output of ensemble learning and model fusion methods as a way to reduce biases and lift model complexity., Comment: 11 pages

Python, as a multi-paradigm language known for its ease of integration with other languages, has gained significant attention among verification engineers recently. A Python-based verification environment capitalizes on open-source frameworks such as PyUVM providing Python-based UVM 1.2 implementation and PyVSC facilitating constrained randomization and functional coverage. These libraries play a pivotal role in expediting test development and hold promise for reducing setup costs. The goal of this paper is to evaluate the effectiveness of PyUVM verification testbenches across various design IPs, aiming for a comprehensive comparison of their features and performance metrics with the established SystemVerilog-UVM methodology., Comment: Published in DVCon U.S. 2024

Being the most widely used language across the world due to its simplicity and with 35 keywords (v3.7), Python attracts both hardware and software engineers. Python-based verification environment leverages open-source libraries such as cocotb and cocotb-coverage that enables interfacing the tesbenches with any available simulator and facilitating constrained randomization, coverage respectively. These libraries significantly ease the development of testbenches and have the potential to reduce the setup cost. The goal of this paper is to assess the effectiveness of a Python-Cocotb verification setup with design IPs and compare its features and performance metrics with the current de-facto hardware verification language i.e., SystemVerilog., Comment: Published in DVCon Europe 2023

We present the Sloan Digital Sky Survey V (SDSS-V) Local Volume Mapper (LVM). The LVM is an integral-field spectroscopic survey of the Milky Way, Magellanic Clouds, and of a sample of local volume galaxies, connecting resolved pc-scale individual sources of feedback to kpc-scale ionized interstellar medium (ISM) properties. The 4-year survey covers the southern Milky Way disk at spatial resolutions of 0.05 to 1 pc, the Magellanic Clouds at 10 pc resolution, and nearby large galaxies at larger scales totaling $>4300$ square degrees of sky, and more than 55M spectra. It utilizes a new facility of alt-alt mounted siderostats feeding 16 cm refractive telescopes, lenslet-coupled fiber-optics, and spectrographs covering 3600-9800A at R ~ 4000. The ultra-wide field IFU has a diameter of 0.5 degrees with 1801 hexagonally packed fibers of 35.3 arcsec apertures. The siderostats allow for a completely stationary fiber system, avoiding instability of the line spread function seen in traditional fiber feeds. Scientifically, LVM resolves the regions where energy, momentum, and chemical elements are injected into the ISM at the scale of gas clouds, while simultaneously charting where energy is being dissipated (via cooling, shocks, turbulence, bulk flows, etc.) to global scales. This combined local and global view enables us to constrain physical processes regulating how stellar feedback operates and couples to galactic kinematics and disk-scale structures, such as the bar and spiral arms, as well as gas in- and out-flows., Comment: 29 pages, 12 figures, accepted for publication in The Astronomical Journal

Art reinterpretation is the practice of creating a variation of a reference work, making a paired artwork that exhibits a distinct artistic style. We ask if such an image pair can be used to customize a generative model to capture the demonstrated stylistic difference. We propose Pair Customization, a new customization method that learns stylistic difference from a single image pair and then applies the acquired style to the generation process. Unlike existing methods that learn to mimic a single concept from a collection of images, our method captures the stylistic difference between paired images. This allows us to apply a stylistic change without overfitting to the specific image content in the examples. To address this new task, we employ a joint optimization method that explicitly separates the style and content into distinct LoRA weight spaces. We optimize these style and content weights to reproduce the style and content images while encouraging their orthogonality. During inference, we modify the diffusion process via a new style guidance based on our learned weights. Both qualitative and quantitative experiments show that our method can effectively learn style while avoiding overfitting to image content, highlighting the potential of modeling such stylistic differences from a single image pair., Comment: project page: https://paircustomization.github.io/

In safety-critical systems that interface with the real world, the role of uncertainty in decision-making is pivotal, particularly in the context of machine learning models. For the secure functioning of Cyber-Physical Systems (CPS), it is imperative to manage such uncertainty adeptly. In this research, we focus on the development of a vehicle's lateral control system using a machine learning framework. Specifically, we employ a Bayesian Neural Network (BNN), a probabilistic learning model, to address uncertainty quantification. This capability allows us to gauge the level of confidence or uncertainty in the model's predictions. The BNN based controller is trained using simulated data gathered from the vehicle traversing a single track and subsequently tested on various other tracks. We want to share two significant results: firstly, the trained model demonstrates the ability to adapt and effectively control the vehicle on multiple similar tracks. Secondly, the quantification of prediction confidence integrated into the controller serves as an early-warning system, signaling when the algorithm lacks confidence in its predictions and is therefore susceptible to failure. By establishing a confidence threshold, we can trigger manual intervention, ensuring that control is relinquished from the algorithm when it operates outside of safe parameters., Comment: arXiv admin note: substantial text overlap with arXiv:2303.08187

The Handwritten Text Recognition problem has been a challenge for researchers for the last few decades, especially in the domain of computer vision, a subdomain of pattern recognition. Variability of texts amongst writers, cursiveness, and different font styles of handwritten texts with degradation of historical text images make it a challenging problem. Recognizing scanned document images in neural network-based systems typically involves a two-step approach: segmentation and recognition. However, this method has several drawbacks. These shortcomings encompass challenges in identifying text regions, analyzing layout diversity within pages, and establishing accurate ground truth segmentation. Consequently, these processes are prone to errors, leading to bottlenecks in achieving high recognition accuracies. Thus, in this study, we present an end-to-end paragraph recognition system that incorporates internal line segmentation and gated convolutional layers based encoder. The gating is a mechanism that controls the flow of information and allows to adaptively selection of the more relevant features in handwritten text recognition models. The attention module plays an important role in performing internal line segmentation, allowing the page to be processed line-by-line. During the decoding step, we have integrated a connectionist temporal classification-based word beam search decoder as a post-processing step. In this work, we have extended existing LexiconNet by carefully applying and utilizing gated convolutional layers in the existing deep neural network. Our results at line and page levels also favour our new GatedLexiconNet. This study reported character error rates of 2.27% on IAM, 0.9% on RIMES, and 2.13% on READ-16, and word error rates of 5.73% on IAM, 2.76% on RIMES, and 6.52% on READ-2016 datasets.

Knowledge graphs (KGs) serve as powerful tools for organizing and representing structured knowledge. While their utility is widely recognized, challenges persist in their automation and completeness. Despite efforts in automation and the utilization of expert-created ontologies, gaps in connectivity remain prevalent within KGs. In response to these challenges, we propose an innovative approach termed ``Medical Knowledge Graph Automation (M-KGA)". M-KGA leverages user-provided medical concepts and enriches them semantically using BioPortal ontologies, thereby enhancing the completeness of knowledge graphs through the integration of pre-trained embeddings. Our approach introduces two distinct methodologies for uncovering hidden connections within the knowledge graph: a cluster-based approach and a node-based approach. Through rigorous testing involving 100 frequently occurring medical concepts in Electronic Health Records (EHRs), our M-KGA framework demonstrates promising results, indicating its potential to address the limitations of existing knowledge graph automation techniques., Comment: 18 pages, 5 figures

Model customization introduces new concepts to existing text-to-image models, enabling the generation of the new concept in novel contexts. However, such methods lack accurate camera view control w.r.t the object, and users must resort to prompt engineering (e.g., adding "top-view") to achieve coarse view control. In this work, we introduce a new task -- enabling explicit control of camera viewpoint for model customization. This allows us to modify object properties amongst various background scenes via text prompts, all while incorporating the target camera pose as additional control. This new task presents significant challenges in merging a 3D representation from the multi-view images of the new concept with a general, 2D text-to-image model. To bridge this gap, we propose to condition the 2D diffusion process on rendered, view-dependent features of the new object. During training, we jointly adapt the 2D diffusion modules and 3D feature predictions to reconstruct the object's appearance and geometry while reducing overfitting to the input multi-view images. Our method outperforms existing image editing and model personalization baselines in preserving the custom object's identity while following the input text prompt and the object's camera pose., Comment: project page: https://customdiffusion360.github.io

Model explanations improve the transparency of black-box machine learning (ML) models and their decisions; however, they can also be exploited to carry out privacy threats such as membership inference attacks (MIA). Existing works have only analyzed MIA in a single "what if" interaction scenario between an adversary and the target ML model; thus, it does not discern the factors impacting the capabilities of an adversary in launching MIA in repeated interaction settings. Additionally, these works rely on assumptions about the adversary's knowledge of the target model's structure and, thus, do not guarantee the optimality of the predefined threshold required to distinguish the members from non-members. In this paper, we delve into the domain of explanation-based threshold attacks, where the adversary endeavors to carry out MIA attacks by leveraging the variance of explanations through iterative interactions with the system comprising of the target ML model and its corresponding explanation method. We model such interactions by employing a continuous-time stochastic signaling game framework. In our framework, an adversary plays a stopping game, interacting with the system (having imperfect information about the type of an adversary, i.e., honest or malicious) to obtain explanation variance information and computing an optimal threshold to determine the membership of a datapoint accurately. First, we propose a sound mathematical formulation to prove that such an optimal threshold exists, which can be used to launch MIA. Then, we characterize the conditions under which a unique Markov perfect equilibrium (or steady state) exists in this dynamic system. By means of a comprehensive set of simulations of the proposed game model, we assess different factors that can impact the capability of an adversary to launch MIA in such repeated interaction settings., Comment: arXiv admin note: text overlap with arXiv:2202.02659

We present the third data release of JADES, the JWST Advanced Deep Extragalactic Survey, providing both imaging and spectroscopy in the two GOODS fields. Spectroscopy consists of medium-depth and deep NIRSpec/MSA spectra of 4,000 targets, covering the spectral range 0.6-5.3 $\mu$m and observed with both the low-dispersion prism (R=30-300) and all three medium-resolution gratings (R=500-1,500). We describe the observations, data reduction, sample selection, and target allocation. We measured 2,375 redshifts (2,053 from multiple emission lines); our targets span the range from z=0.5 up to z=13, including 404 at z>5. The data release includes 2-d and 1-d fully reduced spectra, with slit-loss corrections and background subtraction optimized for point sources. We also provide redshifts and S/N>5 emission-line flux catalogs for the prism and grating spectra, and concise guidelines on how to use these data products. Alongside spectroscopy, we are also publishing fully calibrated NIRCam imaging, which enables studying the JADES sample with the combined power of imaging and spectroscopy. Together, these data provide the largest statistical sample to date to characterize the properties of galaxy populations in the first billion years after the Big Bang., Comment: 41 pages, 26 figures, 10 tables. Submitted to ApJS

$\require{mediawiki-texvc}$Given the sensitivity of the resonant Lyman-$\mathrm{\alpha}$ (Ly$\mathrm{\alpha}$) transition to absorption by neutral hydrogen, observations of Ly$\mathrm{\alpha}$ emitting galaxies (LAEs) have been widely used to probe the ionising capabilities of reionisation-era galaxies and their impact on the intergalactic medium (IGM). However, prior to JWST our understanding of the contribution of fainter sources and of ionised `bubbles' at earlier stages of reionisation remained uncertain. Here, we present the characterisation of three exceptionally distant LAEs at $z>8$, newly discovered by JWST/NIRSpec in the JADES survey. These three similarly bright ($M_\text{UV} \approx -20\,\mathrm{mag}$) LAEs exhibit small Ly$\mathrm{\alpha}$ velocity offsets from the systemic redshift, $\Delta v_\mathrm{Ly\alpha} \lesssim 200\,\mathrm{km\,s^{-1}}$, yet span a range of Ly$\mathrm{\alpha}$ equivalent widths ($15\,\AA$, $31\,\AA$, and $132\,\AA$). The former two show moderate Ly$\mathrm{\alpha}$ escape fractions ($f_\mathrm{esc,Ly\alpha} \approx 10\%$), whereas Ly$\mathrm{\alpha}$ escapes remarkably efficiently from the third ($f_\mathrm{esc,Ly\alpha} \approx 71\%$), which moreover is very compact (half-light radius of $90\pm10\,\mathrm{pc}$). We find these LAEs are low-mass galaxies dominated by very recent, vigorous bursts of star formation accompanied by strong nebular emission from metal-poor gas. We infer the two LAEs with modest $f_\mathrm{esc,Ly\alpha}$, one of which reveals evidence for ionisation by an active galactic nucleus, may have reasonably produced small ionised bubbles preventing complete IGM absorption of Ly$\mathrm{\alpha}$. The third, however, requires a $\sim 3\,\text{physical Mpc}$ bubble, indicating faint galaxies have contributed significantly. The most distant LAEs thus continue to be powerful observational probes into the earlier stages of reionisation., Comment: 23 pages, 12 figures, submitted to MNRAS. Comments welcome

The rise of Transformer architectures has revolutionized medical image segmentation, leading to hybrid models that combine Convolutional Neural Networks (CNNs) and Transformers for enhanced accuracy. However, these models often suffer from increased complexity and overlook the interplay between spatial and channel features, which is vital for segmentation precision. We introduce LHU-Net, a streamlined Hybrid U-Net for volumetric medical image segmentation, designed to first analyze spatial and then channel features for effective feature extraction. Tested on five benchmark datasets (Synapse, LA, Pancreas, ACDC, BRaTS 2018), LHU-Net demonstrated superior efficiency and accuracy, notably achieving a 92.66 Dice score on ACDC with 85\% fewer parameters and a quarter of the computational demand compared to leading models. This performance, achieved without pre-training, extra data, or model ensembles, sets new benchmarks for computational efficiency and accuracy in segmentation, using under 11 million parameters. This achievement highlights that balancing computational efficiency with high accuracy in medical image segmentation is feasible. Our implementation of LHU-Net is freely accessible to the research community on GitHub (https://github.com/xmindflow/LHUNet).

We describe new ultra-deep James Webb Space Telescope (JWST) NIRSpec PRISM and grating spectra for the galaxies JADES-GS-z11-0 ($z_{\mathrm{spec}} = 11.122^{+0.005}_{-0.003}$) and JADES-GS-z13-0 ($z_{\mathrm{spec}} = 13.20^{+0.03}_{-0.04}$), the most distant spectroscopically-confirmed galaxy discovered in the first year of JWST observations. The extraordinary depth of these observations (75 hours and 56 hours, respectively) provides a unique opportunity to explore the redshifts, stellar properties, UV magnitudes, and slopes for these two sources. For JADES-GS-z11-0, we find evidence for multiple emission lines, including [\ion{O}{2}]$\lambda\lambda3726,3729$\AA and [\ion{Ne}{3}$]\lambda3869$\AA, resulting in a spectroscopic redshift we determine with 94\% confidence. We present stringent upper limits on the emission line fluxes and line equivalent widths for JADES-GS-z13-0. At this spectroscopic redshift, the Lyman-$\alpha$ break in JADES-GS-z11-0 can be fit with a damped Lyman-$\alpha$ absorber with $\log{(N_\mathrm{HI}/\mathrm{cm}^{-2})} = 22.42^{+0.093}_{-0.120}$. These results demonstrate how neutral hydrogen fraction and Lyman-damping wings may impact the recovery of spectroscopic redshifts for sources like these, providing insight into the overprediction of the photometric redshifts seen for distant galaxies observed with JWST. In addition, we analyze updated NIRCam photometry to calculate the morphological properties of these resolved sources, and find a secondary source $0.3^{\prime\prime}$ south of JADES-GS-z11-0 at a similar photometric redshift, hinting at how galaxies grow through interactions in the early Universe., Comment: 34 pages, 19 figures, accepted for publication in The Astrophysical Journal (September 30, 2024)

We report the chemical abundance pattern of GS\_3073, a galaxy at $z=5.55$ which was previously confirmed to host an overmassive active black hole, by leveraging the detection of about 40 emission lines, combining JWST/NIRSpec observations and ground-based (VLT/VIMOS) data. Based on the rest-frame UV emission lines, which trace high-density ($\sim 10^5~{\rm cm}^{-3}$) and highly ionized gas, we derived an abundance ratio of $\rm log(N/O) = 0.42^{+0.13}_{-0.10}$. At an estimated metallicity of $0.2~Z_{\odot}$, this is the most extreme nitrogen-rich object found by JWST thus far. In comparison, the relative carbon abundance derived from the rest-frame UV emission lines is $\rm log(C/O) = -0.38^{+0.13}_{-0.11}$, which is not significantly higher than those in local galaxies and stars with similar metallicities. We also found potential detection of coronal lines including [FeVII]$\lambda 6087$ and [FeXIV]$\lambda 5303$, both blended with [CaV]. We inferred a range of Fe abundances compatible with those in local stars and galaxies. Overall, the chemical abundance pattern of GS\_3073 is compatible with enrichment by super-massive stars with $M_* \gtrsim 1000~M_\odot$, asymptotic giant branch (AGB) stars, or Wolf-Rayet (WR) stars. Interestingly, when using optical emission lines which trace lower density ($\sim 10^3~{\rm cm}^{-3}$) and lower ionization gas, we found a sub-solar N/O ratio. We interpret the difference in N/O derived from UV lines and optical lines as evidence for a stratified system, where the inner and denser region is both more chemically enriched and more ionized. Taking this luminous, well-studied system as a benchmark, our results suggest that nitrogen loudness in high-$z$ galaxies is confined to the central, dense, and highly ionized region of the galaxies, while the bulk of the galaxies evolves more normally., Comment: 28 pages, 15 figures, accepted for publication in MNRAS

Permissioned blockchains have been proposed for a variety of use cases that require decentralization yet address enterprise requirements that permissionless blockchains to date cannot satisfy -- particularly in terms of performance. However, popular permissioned blockchains still exhibit a relatively low maximum throughput in comparison to established centralized systems. Consequently, researchers have conducted several benchmarking studies on different permissioned blockchains to identify their limitations and -- in some cases -- their bottlenecks in an attempt to find avenues for improvement. Yet, these approaches are highly heterogeneous, difficult to compare, and require a high level of expertise in the implementation of the underlying specific blockchain. In this paper, we develop a more unified and graphical approach for identifying bottlenecks in permissioned blockchains based on a systematic review of related work, experiments with the Distributed Ledger Performance Scan (DLPS), and an extension of its graphical evaluation functionalities. We conduct in-depth case studies on Hyperledger Fabric and Quorum, two widely used permissioned blockchains with distinct architectural designs, demonstrating the adaptability of our framework across different blockchains. We provide researchers and practitioners working on evaluating or improving permissioned blockchains with a toolkit, guidelines on what data to document, and insights on how to proceed in the search process for bottlenecks.

To study the chemical evolution across cosmic epochs, we investigate Ne, S, Cl, and Ar abundance patterns in the COS Legacy Archive Spectroscopic SurveY (CLASSY). CLASSY comprises local star-forming galaxies (0.02 < z < 0.18) with enhanced star-formation rates, making them strong analogues to high-z star-forming galaxies. With direct measurements of electron temperature, we derive accurate ionic abundances for all elements and assess ionization correction factors (ICFs) to account for unseen ions and derive total abundances. We find Ne/O, S/O, Cl/O, and Ar/O exhibit constant trends with gas-phase metallicity for 12+log(O/H) < 8.5 but significant correlation for Ne/O and Ar/O with metallicity for 12+log(O/H) > 8.5, likely due to ICFs. Thus, applicability of the ICFs to integrated spectra of galaxies could bias results, underestimating true abundance ratios. Using CLASSY as a local reference, we assess the evolution of Ne/O, S/O, and Ar/O in galaxies at z>3, finding no cosmic evolution of Ne/O, while the lack of direct abundance determinations for S/O and Ar/O can bias the interpretation of the evolution of these elements. We determine the fundamental metallicity relationship (FMR) for CLASSY and compare to the high-redshift FMR, finding no evolution. Finally, we perform the first mass-neon relationship analysis across cosmic epochs, finding a slight evolution to high Ne at later epochs. The robust abundance patterns of CLASSY galaxies and their broad range of physical properties provide essential benchmarks for interpreting the chemical enrichment of the early galaxies observed with the JWST., Comment: Accepted for publication in The Astrophysical Journal. 20 pages (main body), 10 figures, 6 Tables

The Near-infrared Spectrograph (NIRSpec) on the James Webb Space Telescope is uniquely suited to studying galaxies in the distant Universe with its combination of multi-object capabilities and sensitivity over a large range in wavelength (0.6-5.3 microns). Here we present the NIRSpec Wide survey, part of the NIRSpec Instrument Science Team's Guaranteed Time Observations, using NIRSpec's microshutter array to obtain spectra of more than 3200 galaxies at $z>1$ at both low- and high-resolution ($R\approx100$ and 2700) for a total of 105 hours. With 31 pointings covering $\approx$320 arcmin$^2$ across the five CANDELS fields with exquisite ancillary photometry from the Hubble Space Telescope, the NIRSpec Wide survey represents a fast and efficient way of using JWST to probe galaxies in the early Universe. Pointing centers are determined to maximize the observability of the rarest, high-value sources. Subsequently, the microshutter configurations are optimized to observe the maximum number of "census" galaxies with a selection function based primarily on HST/F160W magnitude, photometric/slitless grism redshift, and predicted \ha\ flux tracing the bulk of the galaxy population at cosmic noon ($z_{\rm med}=2.0$). We present details on the survey strategy, the target selection, an outline of the motivating science cases, and discuss upcoming public data releases to the community., Comment: Published in A&A. Data for pointings in AEGIS available for download at https://archive.stsci.edu/hlsp/wide (https://archive.stsci.edu/hlsps/wide/download_scripts/hlsp_wide_jwst_nirspec_all_multi_v1.0_spec-download.sh)

We provide an alternate approach to obtaining expansion formulas on the lines of the well-poised Bailey lemma. We recover results due to Spiridonov and Warnaar and one new formula of this type. These formulas contain an arbitrary sequence as an argument, and are thus flexible in the number of parameters they contain. As a result, we are able to derive $19$ new transformation formulas for elliptic hypergeometric series. These transformation formulas appear to be new even in the basic hypergeometric case, when $p=0$., Comment: 14 pp. Referee comments changed version 2 substantially. In particular, some of the earlier claimed new results were not new. Further, several new results are included, which were motivated by referee's remarks

Deep Learning (DL) models have become crucial in digital transformation, thus raising concerns about their intellectual property rights. Different watermarking techniques have been developed to protect Deep Neural Networks (DNNs) from IP infringement, creating a competitive field for DNN watermarking and removal methods. The predominant watermarking schemes use white-box techniques, which involve modifying weights by adding a unique signature to specific DNN layers. On the other hand, existing attacks on white-box watermarking usually require knowledge of the specific deployed watermarking scheme or access to the underlying data for further training and fine-tuning. We propose DeepEclipse, a novel and unified framework designed to remove white-box watermarks. We present obfuscation techniques that significantly differ from the existing white-box watermarking removal schemes. DeepEclipse can evade watermark detection without prior knowledge of the underlying watermarking scheme, additional data, or training and fine-tuning. Our evaluation reveals that DeepEclipse excels in breaking multiple white-box watermarking schemes, reducing watermark detection to random guessing while maintaining a similar model accuracy as the original one. Our framework showcases a promising solution to address the ongoing DNN watermark protection and removal challenges., Comment: To appear in the 33rd USENIX Security Symposium, August 2024, Philadelphia, PA, USA. 18 pages, 7 figures, 4 tables, 5 algorithms, 13 equations

We present rest-frame optical data of the z~4 sub-millimeter galaxy GN20 obtained with JWST/NIRSpec in integral field spectroscopy (IFS) mode. The H$\alpha$ emission is asymmetric and clumpy and extends over a projected distance of more than 15 kpc. To first order, the large-scale ionised gas kinematics are consistent with a turbulent ($\sigma\sim90$ km/s), rotating disc ($v_{\rm rot}\sim500$ km/s), congruent with previous studies of its molecular and ionised gas kinematics. However, we also find clear evidence for non-circular motions in the H$\alpha$ kinematics. We discuss their possible connection with various scenarios, such as external perturbations, accretion or radial flows. In the centre of GN20, we find broad line emission (FWHM $\sim1000-2000$ km/s) in the H$\alpha$+[N II] complex, suggestive of fast, AGN-driven winds or, alternatively, of the broad-line region of an active black hole. Elevated values of [N II]$\lambda6583$/H$\alpha>0.4$ and EW(H$\alpha)>6$ \r{A}, throughout large parts of GN20 suggest that feedback from the active black hole is able to photo-ionise the interstellar medium. Our data corroborates that GN20 offers a unique opportunity to observe key processes in the evolution of the most massive present-day galaxies acting in concert, over 12 billion years ago., Comment: 12 pages, 8 figures; accepted for publication in MNRAS; doi:10.1093/mnras/stae1993

We present the timing solution for the 5.31-ms spider millisecond pulsar (MSP) J1242-4712, discovered with the GMRT. PSR J1242-4712 orbits a companion of minimum mass 0.08 M$_{\odot}$ with an orbital period of 7.7 hrs and occupies a relatively unexplored region in the orbital period versus companion mass space. We did not detect gamma-ray pulsations for this MSP, and also could not identify the optical counterpart for PSR J1242-4712 in available optical/near-infrared data. The profile of J1242-4712 evolves with frequency showing a clear single component at lower frequencies and a three-component profile at 650 MHz. PSR J1242-4712 eclipses for a very short duration near superior conjunction (orbital phase ~ 0.23-0.25) below 360 MHz. Moreover, significant DM delays and errors in pulse times of arrivals are observed near inferior conjunction (orbital phase ~ 0.7), along with an observed eclipse in one epoch at 650 MHz. Observed eclipses and significant orbital period variability suggest that PSR J1242-4712 is possibly not a He-WD binary, but has a semi or non-degenerate companion, indicating that this is a ``spider" MSP lying in a region between typical black widows and redbacks. This system may represent a distinct category of spider MSPs, displaying characteristics that bridge the gap between known black widow and redback MSPs., Comment: 13 pages, 8 figures, 2 tables. Accepted for publication in The Astrophysical Journal

Recent developments in the 2D materials laid emphasis on finding the materials with robust properties for variety of applications including the energy harvesting. The recent discovery of Janus monolayers with broken symmetry has opened up new options for engineering the properties of 2D layered materials. Present study focuses on enhancing thermoelectric properties of 2H-ISbTe 2D Janus monolayer. All the calculations have been performed using fully relaxed unit cell and employing the pseudo potential based quantum espresso code. Calculated structural parameters are in good agreement with previous literature reports. The lattice dynamics calculations predicts this monolayer can withstand a strain of up to 4% beyond which imaginary frequencies appear in the phonon dispersion curves. Computed electronic structure reveals that the monolayer is an indirect wide bandgap material and the bandgap decreases with tensile strain. Furthermore, the computed thermoelectric properties show that the studied monolayer has high Seebeck coefficient of ~ 300 {\mu}V/K and low thermal conductivity which yields reasonably high ZT of ~ 1.31 for a strain of 2% at 300 K with p-type doping. Therefore, our study signifies the fact that tensile strain and p-type doping of 2D Janus monolayer ISbTe can enhance ZT from 0.87 to 1.31 at room temperature which makes it a promising candidate for thermoelectric applications., Comment: 18 pages, 8 figures, Comments are Welcome

Stellar feedback in dwarf galaxies remains, to date, poorly explored, yet is crucial to understanding galaxy evolution in the early Universe. In particular, pre-supernova feedback has recently been found to play a significant role in regulating and disrupting star formation in larger spiral galaxies, but it remains uncertain if it also plays this role in dwarfs. We study the ionised gas properties and stellar content of individual star-forming regions across three nearby, low-metallicity, dwarf starburst galaxies (J0921, KKH046, and Leo P) to investigate how massive stars influence their surroundings and how this influence changes as a function of environment. To achieve this, we extracted integrated spectra of 30 HII regions from archival VLT/MUSE integral field spectroscopic observations of these three dwarf starburst galaxies. We fitted the HII regions' main emission lines with Gaussian profiles to derive their oxygen abundances, electron densities, and luminosities, and we used the Stochastically Lighting Up Galaxies (SLUG) code to derive the stellar mass, age, and bolometric luminosity of the stellar populations driving the HII regions. We then quantified two pre-supernova stellar feedback mechanisms, namely the direct radiation pressure and photoionisation feedback, and explored how feedback strength varies with HII region properties. Our findings suggest that stellar feedback has less of an impact on evolved regions, with both the pressure of the ionised gas and the direct radiation pressure decreasing as a function of HII region size. We also find that these stellar feedback mechanisms are dependent on the metallicity of the HII regions. These findings extend results from stellar feedback studies of more massive star-forming galaxies to the low-mass, low-metallicity regime., Comment: The paper has been published in A&A

This paper is concerned with the problem of sampling and interpolation involving derivatives in shift-invariant spaces and the error analysis of the derivative sampling expansions for fundamentally large classes of functions. A new type of polynomials based on derivative samples is introduced, which is different from the Euler-Frobenius polynomials for the multiplicity $r>1$. A complete characterization of uniform sampling with derivatives is given using Laurent operators. The rate of approximation of a signal (not necessarily continuous) by the derivative sampling expansions in shift-invariant spaces generated by compactly supported functions is established in terms of $L^p$- average modulus of smoothness. Finally, several typical examples illustrating the various problems are discussed in detail., Comment: 34 pages, 24 figures

Rhenium-based superconductors have recently attracted significant interest due to their unconventional superconducting properties. In this work, we report the synthesis and properties of new superconducting Re$_{7}$X$_{3}$ (X = Nb, Ta, Ti, Zr, Hf) binary alloys which maintain a fixed composition of rhenium while crystallizing in centrosymmetric to non-centrosymmetric crystal structures, depending on the elements of the X site. Comprehensive structural and superconducting properties were investigated using powder x-ray diffraction, AC transport, magnetization, and specific heat measurements, and on the basis of these measurements, the superconducting phase diagram was constructed. The results suggest a complex interplay of crystal structure and the Re/X ratio, which governs the strength of spin-orbital coupling and controls the unconventional superconducting behavior in Re-based superconductors., Comment: 8 pages, 9 figure

JWST has recently sparked a new era of Ly$\alpha$ spectroscopy, delivering the first measurements of the Ly$\alpha$ escape fraction and velocity profile in typical galaxies at $z\simeq6-10$. These observations offer new prospects for insight into the earliest stages of reionization. But to realize this potential, we need robust models of Ly$\alpha$ properties in galaxies at $z\simeq5-6$ when the IGM is mostly ionized. Here we use new JWST observations from the JADES and FRESCO surveys combined with VLT/MUSE and Keck/DEIMOS data to characterize statistical distributions of Ly$\alpha$ velocity offsets, escape fractions, and EWs in $z\simeq5-6$ galaxies. We find that galaxies with large Ly$\alpha$ escape fractions (> 0.2) are common at $z\simeq5-6$, comprising 30 per cent of Lyman break selected samples. Comparing to literature studies, our census suggests that Ly$\alpha$ becomes more prevalent in the galaxy population toward higher redshift from $z\sim3$ to $z\sim6$, although we find that this evolution slows considerably between $z\sim5$ and $z\sim6$, consistent with modest attenuation from residual HI in the mostly ionized IGM at $z\simeq5-6$. We find significant evolution in Ly$\alpha$ velocity profiles between $z\simeq2-3$ and $z\simeq5-6$, likely reflecting the influence of resonant scattering from residual intergalactic HI on the escape of Ly$\alpha$ emission near line center. This effect will make it challenging to use Ly$\alpha$ peak offsets as a probe of Lyman continuum leakage at $z\simeq5-6$. We use our $z\simeq5-6$ Ly$\alpha$ distributions to make predictions for typical Ly$\alpha$ properties at $z\gtrsim8$ and discuss implications of a recently-discovered Ly$\alpha$ emitter at $z\simeq8.5$ with a small peak velocity offset (156 km s$^{-1}$)., Comment: 31 pages, 12 figures, accepted by MNRAS